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Enhancing the Privacy of Federated Learning with Sketching [article]

Zaoxing Liu, Tian Li, Virginia Smith, Vyas Sekar
2019 arXiv   pre-print
In response to growing concerns about user privacy, federated learning has emerged as a promising tool to train statistical models over networks of devices while keeping data localized. Federated learning methods run training tasks directly on user devices and do not share the raw user data with third parties. However, current methods still share model updates, which may contain private information (e.g., one's weight and height), during the training process. Existing efforts that aim to
more » ... the privacy of federated learning make compromises in one or more of the following key areas: performance (particularly communication cost), accuracy, or privacy. To better optimize these trade-offs, we propose that sketching algorithms have a unique advantage in that they can provide both privacy and performance benefits while maintaining accuracy. We evaluate the feasibility of sketching-based federated learning with a prototype on three representative learning models. Our initial findings show that it is possible to provide strong privacy guarantees for federated learning without sacrificing performance or accuracy. Our work highlights that there exists a fundamental connection between privacy and communication in distributed settings, and suggests important open problems surrounding the theoretical understanding, methodology, and system design of practical, private federated learning.
arXiv:1911.01812v1 fatcat:mquqgd2ykjepdidtf5bx4rkkpq

Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams [article]

Antonis Manousis, Zhuo Cheng, Ran Ben Basat, Zaoxing Liu, Vyas Sekar
2022 arXiv   pre-print
Today's large-scale services (e.g., video streaming platforms, data centers, sensor grids) need diverse real-time summary statistics across multiple subpopulations of multidimensional datasets. However, state-of-the-art frameworks do not offer general and accurate analytics in real time at reasonable costs. The root cause is the combinatorial explosion of data subpopulations and the diversity of summary statistics we need to monitor simultaneously. We present Hydra, an efficient framework for
more » ... ltidimensional analytics that presents a novel combination of using a "sketch of sketches" to avoid the overhead of monitoring exponentially-many subpopulations and universal sketching to ensure accurate estimates for multiple statistics. We build Hydra as an Apache Spark plugin and address practical system challenges to minimize overheads at scale. Across multiple real-world and synthetic multidimensional datasets, we show that Hydra can achieve robust error bounds and is an order of magnitude more efficient in terms of operational cost and memory footprint than existing frameworks (e.g., Spark, Druid) while ensuring interactive estimation times.
arXiv:2208.04927v1 fatcat:hpjsi2vnjracdjkwqpalabiqr4

Energy Efficiency Optimization Based on Power Allocation in Massive MIMO Downlink Systems

Hongmei Liu, Honggui Deng, Yougen Yi, Zaoxing Zhu, Gang Liu, Jie Zhang
2022 Symmetry  
To solve the energy efficiency (EE) optimization in a multi-cell (MU) massive multiple-input multiple-output (MIMO) downlink system, of which channels are of symmetry in the Time-Division Duplex (TDD) protocol, we utilize a spatially correlated channel model and adopt the minimum mean-squared error (MMSE) estimator to tailor linear precoding vectors. Then, we derive the expression of downlink spectral efficiency (SE), taking interference into account. Subsequently, we establish the EE
more » ... on function, which is defined as the average capacity divided by power consumption. In an interference-limited scenario, the EE optimization is of high complexity to solve globally as it is not jointly concave. To this end, we propose the Dinkelbach-like power allocation algorithm to obtain a suboptimal solution. We transform the EE problem in a fractional form into a subtractive optimization form called an auxiliary subproblem. Then, we relax the sub-problem to a concave problem by initializing the interference and omitting the dynamic power term about throughput. Lastly, we solve iteratively the Karush–Kuhn–Tucker (KKT) conditions by bisection search. Consequently, we obtain a sub-solution with modest complexity. The simulation results justify the rationality of the Dinkelbach-like algorithm and demonstrate that the proposal outperforms the reference schemes and effectively improves the performance metrics EE and SE.
doi:10.3390/sym14061145 fatcat:f7oj4vnhunbvznp4myo552krza

Unleashing In-network Computing on Scientific Workloads [article]

Daehyeok Kim, Ankush Jain, Zaoxing Liu, George Amvrosiadis, Damian Hazen, Bradley Settlemyer, Vyas Sekar
2020 arXiv   pre-print
Many recent efforts have shown that in-network computing can benefit various datacenter applications. In this paper, we explore a relatively less-explored domain which we argue can benefit from in-network computing: scientific workloads in high-performance computing. By analyzing canonical examples of HPC applications, we observe unique opportunities and challenges for exploiting in-network computing to accelerate scientific workloads. In particular, we find that the dynamic and demanding
more » ... of scientific workloads is the major obstacle to the adoption of in-network approaches which are mostly open-loop and lack runtime feedback. In this paper, we present NSinC (Network-accelerated ScIeNtific Computing), an architecture for fully unleashing the potential benefits of in-network computing for scientific workloads by providing closed-loop runtime feedback to in-network acceleration services. We outline key challenges in realizing this vision and a preliminary design to enable acceleration for scientific applications.
arXiv:2009.02457v1 fatcat:musx42cgsvffjerw56rdb2346y

Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms [article]

Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford
2019 arXiv   pre-print
Network performance problems are notoriously difficult to diagnose. Prior profiling systems collect performance statistics by keeping information about each network flow, but maintaining per-flow state is not scalable on resource-constrained NIC and switch hardware. Instead, we propose sketch-based performance monitoring using memory that is sublinear in the number of flows. Existing sketches estimate flow monitoring metrics based on flow sizes. In contrast, performance monitoring typically
more » ... ires combining information across pairs of packets, such as matching a data packet with its acknowledgment to compute a round-trip time. We define a new class of lean algorithms that use memory sublinear in both the size of input data and the number of flows. We then introduce lean algorithms for a set of important statistics, such as identifying flows with high latency, loss, out-of-order, or retransmitted packets. We implement prototypes of our lean algorithms on a commodity programmable switch using the P4 language. Our experiments show that lean algorithms detect ∼82% of top 100 problematic flows among real-world packet traces using just 40KB memory.
arXiv:1911.06951v1 fatcat:wcayufvegjcubbl5lfujtsdzsq

A New Design of Codebook for Hybrid Precoding in Millimeter-Wave Massive MIMO Systems

Gang Liu, Honggui Deng, Kai Yang, Zaoxing Zhu, Jitai Liu, Hu Dong
2021 Symmetry  
The precoding scheme based on codebooks is used to save the same set of codebook in advance at the transmitter and the receiver, then, the receiver selects the most appropriate precoding matrix from codebooks according to different channel state information (CSI). Therefore, the design of codebook plays an important role in the performance of the whole scheme. The symmetry-based hybrid precoder and combiner is a highly energy efficient structure in the millimeter-wave massive multiple-input
more » ... iple-output (MIMO) system, but at the same time, it also has the problems of high bit error rate and low spectral efficiency. In order to improve the spectral efficiency, we formulate the codebook design as a joint optimization problem and propose an iteration algorithm to obtain the enhanced codebook by combining the compressive sampling matching pursuit (CoSaMP) algorithm with the dictionary learning algorithm. In order to prove the validity of the proposed algorithm, we simulate and analyze the change of the spectral efficiency of the algorithm with the signal-to-noise ratio (SNR) and the number of radio frequency (RF) chains of different precoding schemes. The simulation results demonstrate that the spectral efficiency of the algorithm is obviously outstanding compared with that of the OMP-based joint codebook algorithm and the hybrid precoding algorithm with quantization algorithm under low SNR and different numbers of RF chains. Particularly, when SNR is lower than 0 dB, the proposed algorithm performs very close to the optimal unconstrained precoding algorithm.
doi:10.3390/sym13050743 doaj:54549bb3cb874d00a4b1743576961de6 fatcat:ef6f76b6fjdmtbdrtqxm3zpq7e

Hybrid Precoding-Based Millimeter Wave Massive MIMO-NOMA Systems

Zaoxing Zhu, Honggui Deng, Fuxin Xu, Wenjuan Zhang, Gang Liu, Yinhao Zhang
2022 Symmetry  
A symmetry-based hybrid precoder and combiner is a high spectral efficiency structure in millimeter-wave (mmWave) massive multiple-input multiple-output (mMIMO) non-orthogonal multiple access (NOMA) system. To improve the spectral efficiency of the mmWave mMIMO-NOMA system, we first propose a user grouping scheme to suppress the strong inter-user interference caused by NOMA, then the hybrid precoder based on user channel alignment and the zero-forcing algorithm is constructed to further improve
more » ... the signal-to-interference-plus-noise ratio (SINR) of the receiver. Subsequently, the non-convex spectral efficiency optimization problem is transformed into a convex optimization problem of inter-cluster power allocation and the closed-form solution for the optimal power under the minimum rate constraint is obtained by solving the KKT condition to further improve the spectral efficiency. The simulation results show that the proposed scheme can achieve higher spectral efficiency compared to orthogonal multiple access (OMA), fixed power allocation (FPA), K-means, and cluster head selection (CHS).
doi:10.3390/sym14020412 fatcat:edi46apz4zeafmvfhmfha3gd54

DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching [article]

Zaoxing Liu, Zhihao Bai, Zhenming Liu, Xiaozhou Li, Changhoon Kim, Vladimir Braverman, Xin Jin, Ion Stoica
2019 arXiv   pre-print
Load balancing is critical for distributed storage to meet strict service-level objectives (SLOs). It has been shown that a fast cache can guarantee load balancing for a clustered storage system. However, when the system scales out to multiple clusters, the fast cache itself would become the bottleneck. Traditional mechanisms like cache partition and cache replication either result in load imbalance between cache nodes or have high overhead for cache coherence. We present DistCache, a new
more » ... buted caching mechanism that provides provable load balancing for large-scale storage systems. DistCache co-designs cache allocation with cache topology and query routing. The key idea is to partition the hot objects with independent hash functions between cache nodes in different layers, and to adaptively route queries with the power-of-two-choices. We prove that DistCache enables the cache throughput to increase linearly with the number of cache nodes, by unifying techniques from expander graphs, network flows, and queuing theory. DistCache is a general solution that can be applied to many storage systems. We demonstrate the benefits of DistCache by providing the design, implementation, and evaluation of the use case for emerging switch-based caching.
arXiv:1901.08200v2 fatcat:3q4mo7z345a73bdlagryrumxna

New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory

Vladimir Braverman, Zaoxing Liu, Tejasvam Singh, N. V. Vinodchandran, Lin F. Yang
2017 Algorithmica  
Halldórsson, Sun, Szegedy, and Wang (ICALP 2012) [16] investigated the space complexity of the following problem CLIQUE-GAP(r, s): given a graph stream G, distinguish whether ω(G) ≥ r or ω(G) ≤ s, where ω(G) is the clique-number of G. In particular, they give matching upper and lower bounds for CLIQUE-GAP(r, s) for any r and s = c log(n), for some constant c. The space complexity of the CLIQUE-GAP problem for smaller values of s is left as an open question. In this paper, we answer this open
more » ... stion. Specifically, for any r and for s =Õ(log(n)), we prove that the space complexity of CLIQUE-GAP problem isΘ( ms 2 r 2 ). Our lower bound is based on a new connection between graph decomposition theory (Chung, Erdös, and Spencer [11], and Chung [10]) and the multiparty set disjointness problem in communication complexity. Definition 1. CLIQUE-GAP(r, s): given a graph stream G, integer r and s with 0 ≤ s ≤ r, output "1" if G has a r-clique or "0" if G has no (s+1)-clique. The output can be either 0 or 1 if the size of the max-clique w(G) is in [s + 1, r].
doi:10.1007/s00453-017-0277-5 fatcat:i56eio2vnrb2vperjypsiersnq

Initial Value Acceleration-Based Alternating Minimization Algorithm for Dynamic Sub-Connected Hybrid Precoding in Millimeter Wave MIMO Systems

Jitai Liu, Honggui Deng, Shumin Wang, Gang Liu, Kai Yang, Zaoxing Zhu
2021 Symmetry  
Symmetry-based sub-connected hybrid precoding is an energy-friendly structure in wireless communications. Most of the prior work set a diagonal constraint on the analog precoder and used a randomly set matrix as the initial analog precoder, which did not match the optimal channel conditions, leading to a decrease in spectral efficiency, and some had huge complexity when calculating the digital precoder. Aiming to solve these problems, this paper proposed a low-complexity hybrid precoding
more » ... hm based on Initial value Acceleration-based Alternating Minimization (IAAM). Leveraging the special structure of analog precoder in sub-connected scheme, we design the analog precoder through low-complexity quadratic programming and use the least square method to obtain the digital precoder. Moreover, we design a heuristic algorithm with the objective function of maximizing the effective channel gain to calculate the initial analog precoder as the starting point for alternating minimization. The simulation results show that the spectral efficiency of this algorithm is at least 17.5% higher than the existing two traditional sub-connected algorithms. Additionally, it increases energy efficiency by at least 12.8% compa with the Orthogonal Matching Pursuit (OMP) algorithm. Its algorithm convergence speed is fast, which increases with the number of RF chains.
doi:10.3390/sym13020248 fatcat:2gkq2t6glfcgrmlkkgl4w7j3ui

Towards Fast and Scalable Graph Pattern Mining

Anand Padmanabha Iyer, Zaoxing Liu, Xin Jin, Shivaram Venkataraman, Vladimir Braverman, Ion Stoica
2018 USENIX Workshop on Hot Topics in Cloud Computing  
While there has been a tremendous interest in processing graph-structured data, existing distributed graph processing systems take several minutes or even hours to mine simple patterns on graphs. In this paper, we try to answer the question of whether it is possible to build a graph pattern mining engine that is both fast and scalable. Leveraging the observation that in several pattern mining tasks, providing an approximate answer is good enough, we propose the use of approximation for graph
more » ... tern mining. However, we find that existing approximation techniques do not work for this purpose. Based on this, we present a new approach for approximate graph pattern mining that leverages recent advancements in graph approximation theory. Our preliminary evaluations show encouraging results: compared to state-of-the-art, finding 3-motifs in Twitter graph is 165⇥ faster while incurring only 5% error. We conclude by discussing several systems challenges to make our proposal practical.
dblp:conf/hotcloud/IyerLJVBS18 fatcat:jpyx3432nvfq5affdwffv7t6wi

New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory [chapter]

Vladimir Braverman, Zaoxing Liu, Tejasvam Singh, N. V. Vinodchandran, Lin F. Yang
2015 Lecture Notes in Computer Science  
Halldórsson, Sun, Szegedy, and Wang (ICALP 2012) [16] investigated the space complexity of the following problem CLIQUE-GAP(r, s): given a graph stream G, distinguish whether ω(G) ≥ r or ω(G) ≤ s, where ω(G) is the clique-number of G. In particular, they give matching upper and lower bounds for CLIQUE-GAP(r, s) for any r and s = c log(n), for some constant c. The space complexity of the CLIQUE-GAP problem for smaller values of s is left as an open question. In this paper, we answer this open
more » ... stion. Specifically, for any r and for s =Õ(log(n)), we prove that the space complexity of CLIQUE-GAP problem isΘ( ms 2 r 2 ). Our lower bound is based on a new connection between graph decomposition theory (Chung, Erdös, and Spencer [11], and Chung [10]) and the multiparty set disjointness problem in communication complexity. Definition 1. CLIQUE-GAP(r, s): given a graph stream G, integer r and s with 0 ≤ s ≤ r, output "1" if G has a r-clique or "0" if G has no (s+1)-clique. The output can be either 0 or 1 if the size of the max-clique w(G) is in [s + 1, r].
doi:10.1007/978-3-662-48054-0_13 fatcat:g4db7424crfahl6homfrrvao6m

Energy Efficiency Optimization of Massive MIMO System with Uplink Multi-Cell Based on Imperfect CSI with Power Control

Jie Zhang, Honggui Deng, Youzhen Li, Zaoxing Zhu, Gang Liu, Hongmei Liu
2022 Symmetry  
In order to solve the energy efficiency optimization problem in the uplink multi-cell massive MIMO system, this paper constructs the system transmission model, of which the channel is symmetry, based on user and base station, and deduces the expression of data transmission rate of each user. Then, we establish a model of the spectral and energy efficiency of multi-cell massive MIMO system by analyzing the pilot transmission and channel estimation. We also derive the nonconvex function for the
more » ... ergy efficiency optimization, which is difficult to solve directly. Therefore, we propose an improved particle swarm optimization algorithm to obtain the suboptimal solution, under low complexity, by optimizing the distribution of user power. To demonstrate the advantages of our proposed algorithm, we simulate the energy efficiency performance of the algorithm. The results show that the proposed algorithm can effectively improve the energy efficiency of the system.
doi:10.3390/sym14040780 fatcat:l6khfjdpgbhgjapzpfagefwe7i

SketchLib: Enabling Efficient Sketch-based Monitoring on Programmable Switches

Hun Namkung, Zaoxing Liu, Daehyeok Kim, Vyas Sekar, Peter Steenkiste
2022 Symposium on Networked Systems Design and Implementation  
Sketching algorithms or sketches enable accurate network measurement results with low resource footprints. While emerging programmable switches are an attractive target to get these benefits, current implementations of sketches are either inefficient and/or infeasible on hardware. Our contributions in the paper are: (1) systematically analyzing the resource bottlenecks of existing sketch implementations in hardware; (2) identifying practical and correct-by-construction optimization techniques
more » ... tackle the identified bottlenecks; and (3) designing an easy-to-use library called SketchLib to help developers efficiently implement their sketch algorithms in switch hardware to benefit from these resource optimizations. Our evaluation on state-of-the-art sketches demonstrates that SketchLib reduces the hardware resource footprint up to 96% without impacting fidelity.
dblp:conf/nsdi/NamkungLKSS22 fatcat:o6h4cbtfjvcsrmly6vo3ur6sf4

Streaming Algorithms for Halo Finders

Zaoxing Liu, Nikita Ivkin, Lin Yang, Mark Neyrinck, Gerard Lemson, Alexander Szalay, Vladimir Braverman, Tamas Budavari, Randal Burns, Xin Wang
2015 2015 IEEE 11th International Conference on e-Science  
doi:10.1109/escience.2015.73 dblp:conf/eScience/LiuIYNLSBBBW15 fatcat:flbt2sexo5du7l2aazrxsriffm
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